báo cáo khoa học: " Implementation of case management to reduce cardiovascular disease risk in the Stanford and San Mateo Heart to Heart randomized controlled trial: study protocol and baseline characteristics" pps

Open AccessStudy protocol Implementation of case management to reduce cardiovascular disease risk in the Stanford and San Mateo Heart to Heart randomized controlled trial: study protoc

Open Access

Study protocol

Implementation of case management to reduce cardiovascular

disease risk in the Stanford and San Mateo Heart to Heart

randomized controlled trial: study protocol and baseline

characteristics

Jun Ma*, Ky-Van Lee, Kathy Berra and Randall S Stafford

Address: Program on Prevention Outcomes and Practices, Stanford Prevention Research Center, Stanford University School of Medicine, Stanford,

CA, USA

Email: Jun Ma* - Jun.Ma@stanford.edu; Ky-Van Lee - Ky-van.Lee@stanford.edu; Kathy Berra - kberra@stanford.edu;

Randall S Stafford - rstafford@stanford.edu

* Corresponding author

Abstract

Background: Case management has emerged as a promising alternative approach to supplement

traditional one-on-one sessions between patients and doctors for improving the quality of care in chronic

diseases such as coronary heart disease (CHD) However, data are lacking in terms of its efficacy and

cost-effectiveness when implemented in ethnic and low-income populations

Methods: The Stanford and San Mateo Heart to Heart (HTH) project is a randomized controlled clinical

trial designed to rigorously evaluate the efficacy and cost-effectiveness of a multi-risk cardiovascular case

management program in low-income, primarily ethnic minority patients served by a local county health

care system in California Randomization occurred at the patient level The primary outcome measure is

the absolute CHD risk over 10 years Secondary outcome measures include adherence to guidelines on

CHD prevention practice We documented the study design, methodology, and baseline

sociodemographic, clinical and lifestyle characteristics of 419 participants

Results: We achieved equal distributions of the sociodemographic, biophysical and lifestyle characteristics

between the two randomization groups HTH participants had a mean age of 56 years, 63% were Latinos/

Hispanics, 65% female, 61% less educated, and 62% were not employed Twenty percent of participants

reported having a prior cardiovascular event 10-year CHD risk averaged 18% in men and 13% in women

despite a modest low-density lipoprotein cholesterol level and a high on-treatment percentage at baseline

Sixty-three percent of participants were diagnosed with diabetes and an additional 22% had metabolic

syndrome In addition, many participants had depressed high-density lipoprotein (HDL) cholesterol levels

and elevated values of total cholesterol-to-HDL ratio, triglycerides, triglyceride-to-HDL ratio, and blood

pressure Furthermore, nearly 70% of participants were obese, 45% had a family history of CHD or stroke,

and 16% were current smokers

Conclusion: We have recruited an ethnically diverse, low-income cohort in which to implement a case

management approach and test its efficacy and cost-effectiveness HTH will advance the scientific

understanding of better strategies for CHD prevention among these priority subpopulations and aid in

guiding future practice that will reduce health disparities

Published: 27 September 2006

Received: 24 April 2006 Accepted: 27 September 2006 This article is available from: http://www.implementationscience.com/content/1/1/21

© 2006 Ma et al; licensee BioMed Central Ltd.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Coronary heart disease (CHD) affects 13 million

Ameri-cans and is estimated to have cost the US 142 billion

dol-lars in 2005 [1] The current primary care delivery model

lacks a multidisciplinary infrastructure that is conducive

to effective management of multiple CHD risk factors [2]

The growing strain of chronic disease management on the

health care system leaves physicians little time for

preven-tive care [3], which paradoxically is indispensable for the

treatment and prevention of many chronic diseases

including CHD While CHD affects every racial/ethnic

group and social class, ethnic minorities and persons of

low socioeconomic status (SES) disproportionately bear

the burden of CHD and its major risk factors [1,4], These

population subgroups also are more likely to receive

sub-standard cardiac care compared with whites and

individ-uals of higher SES [5] Accelerating the translation of

research into community-based practice and enhancing

health impact in disparate populations have been

identi-fied as strategic imperatives for the elimination of

inequi-ties in cardiovascular health [6]

Alternative approaches are needed to supplement

tradi-tional one-on-one sessions between patients and doctors

One such approach is integrated care delivered through

case management (CM) Case management is a

compre-hensive, longitudinal approach that involves a

multidisci-plinary team of health care providers, such as physicians,

nurses and dietitians, who simultaneously intervene to

reduce multiple risk factors for a disease, such as CHD

Randomized clinical trials have established the efficacy of

intensive case management intervention to reduce

multi-ple cardiovascular risk factors among predominantly

white, high-risk patients [7-10] Only recently has this

therapeutic approach been tested among ethnic

minori-ties, where it was found to be effective [11] Researchers

have urged greater implementation of case management

[12]

Chronic disease management for ethnic minorities of

low-SES represents unique and difficult challenges for

local health care systems, many of which are

overbur-dened by a complex clinical load and have a primary care

delivery model that is not well designed to provide

inten-sive chronic disease management

The Stanford and San Mateo Heart to Heart (HTH) project

is designed to conduct a randomized controlled clinical

trial that rigorously evaluates the efficacy and

cost-effec-tiveness of a case management intervention in reducing

cardiovascular risk among patients of the San Mateo

County Medical Center (SMMC) in California, U.S.A

Based on outcomes data available through the clinical

trial, HTH staff will then facilitate implementation of the

HTH case management model as an ongoing disease

management program within SMMC This report details the study design, methodology, and baseline sociodemo-graphic, clinical and lifestyle characteristics of 419 rand-omized participants We expect participants to have sociodemographic characteristics that differ significantly from those of the San Mateo County and U.S adult pop-ulations We also anticipate that participants will possess clinical and lifestyle risk factors that predict elevated risk

of future cardiovascular events and that these risk factors can be modified through intense medical and/or lifestyle interventions

Methods

The study was approved by the Stanford Institutional Review Board (IRB) and an independent IRB responsible for reviewing study protocols for the San Mateo Medical Center (SMMC)

Study setting

San Mateo County in California is a study in contrasts – although this mostly suburban county includes some of the most expensive housing in the nation, it has a sizable population of lower-SES persons with demographic char-acteristics comparable to urban areas As of 2004, the racial composition of San Mateo County was 62% White, 26% Asian/Pacific Islander, and 4% Black Twenty-two percent of the population self-identified as Hispanic and 32% as foreign-born [13] Within San Mateo County, heart disease is the leading cause of death (29% of all deaths during 1997–2001) while stroke is third [14] In

2004, 7% of the adult population had diabetes with the highest prevalence (15%) among persons aged 65 and older In addition, 86% of San Mateo County adult resi-dents had reported at least one cardiovascular risk factor,

e.g., 75% for overweight and obesity, 55% for physical

inactivity, 26% for hypertension, 25% for hyperlipidemia, and 12% for smoking As a branch of the county govern-ment, the SMMC serves a significant portion of the county population that has low SES and lacks private health insurance The SMMC has approximately 106 physicians per 100,000 people, whereas the national average was 289/100,000 in 2000

Study design

HTH is a 5-year project that consists of a randomized con-trolled clinical trial in the first 4 years and a transition phase in the last year The 2-armed clinical trial (Immedi-ate vs Delayed Intervention) was designed to enroll 400 patients In an intention-to-treat analysis, this sample size yields 87% power to detect a mean change of 5 points in the Framingham risk score, with an SD of 10, at an α level

of 0.01 after accounting for a 25% loss to follow-up

Participants in both intervention groups continue to receive usual medical care throughout the study period In

addition, participants randomized to Immediate

Inter-vention receive intensive case management for CHD risk

reduction for 15 months and then a maintenance

pro-gram for a minimum of 12 months to assess the durability

of initial intervention changes Participants randomized

to Delayed Intervention serve as control for Immediate

Intervention patients for the first 15 months and then

receive intensive case management for 15 months The

switching-over design not only addresses ethical concerns

about withholding treatment from half the study sample,

but will also enable us to assess whether the intervention

had equal impact whether provided to a nạve population

or to a group followed in usual care for 15 months We

will compare change in CHD risk from baseline to 15

months for Immediate Intervention with that from 15

months to 30 months for Delayed Intervention Similar

magnitudes of change in CHD risk between the two study

arms would imply that the Delayed Intervention arm was

not notably contaminated by the intervention and

meas-urement process and that no noteworthy differences were

caused by the 15-month difference in time per se.

Immediate Intervention patients who complete their

12-month maintenance period and Delayed Intervention

patients who complete their 15-month case management

period remain under maintenance case management until

they are fully transitioned back to the care of the SMMC in

the last year of the project In addition to patient

transi-tion, we will also transition the HTH case management

model, as guided by outcomes data from the clinical trial,

into an ongoing disease management program operated

by SMMC By including this transition phase, we will be

able to assure continuity in patient care and also test the

feasibility and effectiveness of implementing our

inter-vention in a community practice setting

Recruitment

Between October 2003 and April 2005, 1005 patients

were referred by physicians at four SMMC outpatient

clin-ics located in Menlo Park, Redwood City, South San

Fran-cisco, and Daly City These four clinics were chosen for

geographic proximity, accommodating clinic

environ-ment, sufficient patient volume, diverse patient

demo-graphics, and established adult primary care services All

data acquisition and case management visits took place at

the clinic where the patient usually receives his/her

pri-mary care

Physicians at the study clinics were instructed to refer

male and female patients between the ages of 35 and 85

who had CHD, CHD risk equivalents (i.e., abdominal

aortic aneurysm, peripheral vascular disease, carotid

artery disease, or diabetes mellitus), or moderately to

severely elevated levels of major CHD risk factors We

were unable to contact 257 of the 1005 referred patients

and an additional 142 declined participation (Figure 1)

We screened the remaining 596 patients by phone or at the baseline visit and excluded 143 patients for failing to meet the exclusion criteria These criteria identify patients with circumstances that may severely limit their ability complete the study protocol or that may confound results

of the study The footnotes in table 1 list percentages by exclusion criteria During the same phone call, those not excluded were scheduled for a baseline visit Table 1 enu-merates study inclusion and exclusion criteria Consent forms were available in English and Spanish and the patient's informed consent was obtained before the start

of the baseline visit For patients who spoke a language other than English or Spanish, a family member over the age of 18 or a SMMC staff member served as interpreter

As part of the baseline evaluation, biophysical measures were obtained that further excluded 44 patients not meet-ing inclusion criteria

Randomization

A total of 419 patients met all study criteria and provided informed consent They were randomized into Immediate

or Delayed Intervention groups, using the permuted block method stratified by gender and ethnicity (Hispanic vs Non-Hispanic) A statistician independent of the study generated a sequence of 100 randomization IDs and treat-ment assigntreat-ments per clinic for each of the four

combina-tions of gender and ethnicity, i.e 1) female, Hispanic, 2)

male, Hispanic, 3) female, non-Hispanic, and 4) male, non-Hispanic An administrative assistant who is not involved in the study printed the IDs and corresponding treatment assignments on separate pages and sealed each page into an opaque envelope The administrative assist-ant then placed these envelopes by stratification group and in randomization sequence into four envelope con-tainers for use at each clinic All case managers were masked to randomization sequence and treatment assign-ments At the baseline/randomization visit, each eligible and willing participant was instructed to take the enve-lope in the very front of the appropriate container, open the envelope in the presence of the case manager, and read his group randomization The participant would then sign the randomization form and the case manager would record the participant's randomization assignment and the randomization ID number on the randomization dis-position form

Randomization occurred at the patient level in this trial Randomization at the clinic or physician level would cast detrimental doubts on internal validity of the trial as it would not be feasible to guarantee a balanced distribution

of the diversity of clinic sites and physician practice pat-terns across the study arms Consequently, it would be dif-ficult to determine whether outcomes reflected the intervention or differences in patient populations across

sites and differences in physician practice patterns A

drawback of patient-level randomization is the possibility

of contamination We expect the extent and impact of

contamination to be modest, however By design,

study-specific case managers who are independent of existing

physician practices within the study clinic sites provide

case-management to the intervention patients and the

scheduling process is separate from that of the clinical

sites Much of the value of the intervention comes from

activities that are not usually given high priority by

pri-mary care physicians In addition, any potential for

con-tamination produces a conservative bias, reducing the

measured impact of the intervention and biasing the find-ings towards the null hypothesis Furthermore, our statis-tical methods will specifically address the degree of intra-class correlation within physician's practices and thereby assess the likelihood and potential extent of contamina-tion

Study measurements

The primary outcome measure is the absolute CHD risk over 10 years For participants without known CHD, the Framingham risk assessment algorithms published by Wilson et al [33] will be used to estimate the 10-year risk

Enrollment and follow-up in the Stanford and San Mateo County Heart to Heart Trial

Figure 1

Enrollment and follow-up in the Stanford and San Mateo County Heart to Heart Trial 1A patient may be ineligible for more thanone reason 2Number of participants who failed to meet exclusion criteria: being resident in long-term facility (n = 1); mov-ing away soon (26); age ≤ 35 or ≥ 85 (13); significant comorbidities (10); substance abuse (2); no telephone (1); family member already enrolled (7); anticipated absence >4 months (18); difficulty coming to appointments (35); participating in other research programs (21); pregnant or planning to become pregnant (2); no English or Spanish and no interpreter (7) 3Number of partic-ipants who failed to meet inclusion criteria: Has CAD or CAD risk equivalent but did not have any of the CHD risk factors specified in Table 1 (n = 2); does not have CAD or CAD risk equivalent and did not have any of the CHD risk factors specified

in Table 1 (n = 42)

419 Randomized

118 15-month follow up

1 Deceased

7 Moved away

9 Unable to contact

9 Passive refusal

68 In progress

130 15-month follow up

2 Deceased

4 Moved away

9 Unable to contact

5 Passive refusal

57 In progress

1005 Patients referred

586 Total Ineligible 1

143 Failed exclusion 2

44 Failed inclusion3

257 Unable to contact

142 Declined

212 Immediate Intervention

207 Delayed Intervention

probability of CHD on the basis of sex, age, systolic blood

pressure, total cholesterol (TC), cigarette smoking status,

and diabetes status For participants with existing CHD,

their 10-year CHD risk will be extrapolated from 2-year

probability estimates [34] after accounting for aging effect

and censoring individuals with new-onset CHD as time

elapses Secondary guideline-based outcome measures

include low-density lipoprotein cholesterol (LDL-C),

high-density lipoprotein cholesterol (HDL-C), systolic

and diastolic blood pressure, hemoglobin A1c (HbA1c),

physical activity, smoking status, body mass index (BMI),

dietary intake of total and saturated fat and fruits and

veg-etables, use of recommended medications (e.g., aspirin,

statins, thiazide diuretics, beta-blockers, and

angiotensin-converting enzyme inhibitors [ACEIs]/angiotensin

recep-tor blockers [ARBs])

Outcome measurements are designed to occur at baseline

and 15 months for all patients, at 27 months for

Immedi-ate Intervention, and at 30 months for Delayed

Interven-tion patients HTH case managers, including one nurse

practitioner, two registered nurses, and two registered

die-titians, completed all baseline measurements, which

con-sisted of biophysical measurements, and lifestyle, social,

and demographic questionnaires Baseline visits were

conducted in one or two clinic visits, depending upon

patient and case manager schedules

Height was measured by a wall stadiometer and weight by

a digital balance scale Both of these measures were taken without shoes and while wearing light clothing BMI was then calculated (in kg/m2) Waist circumference (in cm) was measured in standing position using a cloth tape measure placed at the level of the iliac crest Blood pres-sure was meapres-sured in both arms, using the brachial artery, after 10 minutes of sitting in a relaxed position, and the average of two readings was used After ascertaining that the patient had fasted for ≥ 12 hours, a finger stick blood sample was obtained for measurement of plasma TC, HDL-C, LDL-C, triglyceride (TG), and glucose levels using the Cholestech LDX point of service testing system (Cholestech Corporation, Hayward, CA) Plasma HbA1c was obtained utilizing the Cholestech GDX

Patients were asked about medical and family history related to cardiovascular disease (CVD) They were asked

to bring all medications, including supplements and nutraceuticals, with them to the baseline visit Medication name, medication class, dosage, and therapeutic purpose were recorded Patients with CHD and/or diabetes were specifically asked about their use of β-blockers, statins, ACEIs/ARBs, and aspirin Health care utilization was assessed by asking about hospitalizations, emergency room visits, and outpatient visits within the past six months

Table 1: Inclusion and exclusion criteria.

Inclusion criteria

The patient has CAD or CAD risk equivalent (abdominal aortic aneurysm, peripheral vascular disease, transient ischemic attack, stroke, diabetes,

or FBS ≥ 126 mg/dL × 2) and has at least one of following: SBP ≥ 130 mmHg, DBP ≥ 80 mmHg, LDL ≥ 100 mg/dL, HDL ≤ 40 mg/dL, TG ≥ 150 mg/

dL, TC ≥ 240 mg/dL, TG ≥ 500 mg/dL, HbA1c ≥ 8.0%, BMI ≥ 35, or is a current smoker.

positive family history of CAD.

Abbreviations: FBS = fasting blood sugar, SBP = systolic blood pressure, DBP = diastolic blood pressure, LDL = low-density lipoprotein, HDL = high-density lipoprotein, BMI = body mass index, TC = total cholesterol, TG = triglycerides, HbA1c = hemoglobin A1c.

Exclusion criteria

Resident of long-term facility.

Moving before end of intervention (30 months).

Age ≤ 35 or ≥ 85.

Significant comorbidities such as: uncontrolled metabolic disorders (renal failure, liver failure, etc.), active symptoms suggesting acute myocardial infarction or decompensated congestive heart failure, Malignancy or other condition limiting life expectancy, psychiatric disorder with active manifestations.

Substance abuse.

No telephone or means of contacting patient.

Family household member already enrolled.

Homeless and not living with relatives/friends.

Anticipated absence for more than 4 consecutive months.

Difficulty coming to appointments approximately every 1–2 months.

Already participating in the Diabetes program.

Currently pregnant or intends to get pregnant the next 3 years.

Case managers recorded patient age, gender, ethnicity (i.e.

Latinos/Hispanics vs others including traditional racial

categories), education, marital status, employment status,

and household size Standardized questionnaires were

administered to collect data on cigarette smoking (short

form of stage of change [15]), nicotine dependence for

current smokers (Fagerstrom Tolerance Questionnaire

[16]), self-perceived health-related quality of life (SF-12

Health Survey [17]), self-reported depression (CES-D

scale [18]), fruit, vegetable and fat intake (Block screeners

[19,20]), and physical activity (Stanford 7-Day Recall

[21])

All baseline measurements are repeated at two follow-up

visits: a first follow-up planned for 15 months and a

sec-ond planned for 27–30 months The 15-month follow-up

measurements are expected to be completed by August

2006 and the 27–30-month follow-up measurements by

October 2007 During follow-up evaluations, case

manag-ers continue to collect all biophysical measurements;

however, questionnaires are administered by trained

research assistants who are masked to treatment

assign-ments Research assistants also are responsible for calling

patients at 7 months and 22 months to obtain interim

data on health care utilization

Intervention

HTH intervention protocols specifically focused on CHD

risk reduction Non-CHD-related conditions remained

the responsibility of the patient's PCP, although we often

facilitated having the primary care provider address

spe-cific patient needs

Immediate intervention

HTH case-management intervention was based on the

lat-est guidelines for the management of CHD risk factors,

particularly those reflecting cholesterol management

[22,23], hypertension [24], physical activity [25], diabetes

[26], aspirin therapy [27,28], smoking [29], obesity

man-agement [30], and primary and secondary CHD

preven-tion [31,32] Specific lifestyle and medical protocols for

case managers were developed from these guidelines and

continue to be updated based on new evidence Each

patient was managed by a nurse practitioner/registered

nurse and a dietitian Guided by the intervention

proto-cols, the intensity of case management was individualized

based on patient risk profile, patient preferences, and

available resources within the community The aim for

each patient was to improve individual risk factors and

reach recommended goals Supervised by two physicians

and a senior nurse practitioner, the case managers

reviewed, adjusted as necessary, and monitored medical

therapies in accordance to guidelines and the SMMC

for-mulary Lifestyle modification was strongly emphasized

as a critical component of achieving CHD prevention

goals In particular, dietary management was emphasized, including recommendation of a low saturated fat (less than 7% of caloric intake), low cholesterol (< 150 mg/ day), mainly plant-based diet with calorie restrictions for overweight/obese persons Stress management and cop-ing skills along with physical activity also was empha-sized, including recommendations of a regular exercise regimen (≥ 30 minutes of moderate intensity on most days) Cigarette smokers were encouraged to join a stop smoking program that may include use of the nicotine patch or other medications Additionally, nicotine replacement pharmacotherapies were prescribed, when appropriate, to current smokers Long-term adherence to these strategies and to medication therapies was stressed and evaluated at each appointment

Delayed intervention

For the first 15 months following randomization, Delayed Intervention patients were expected to continue receiving on-going care from their PCPs They received a folder at the conclusion of the baseline visit including handouts from the American Heart Association containing basic information about cardiovascular disease and a risk factor description sheet listing their biophysical measurements recorded at the baseline appointment as well as the ideal values for each measurement They were told that they would be contacted by phone at 7 months and would begin case management intervention at 15 months In addition, all PCPs received a letter outlining the CHD risk reduction goals recommended in the latest national guidelines

Statistical analysis and hypothesis testing

The primary hypothesis of the trial is that Immediate Intervention participants will experience greater reduc-tions in 10-year CHD risk based on Framingham risk probability (primary outcome) than will Delayed Inter-vention participants To test the primary hypothesis, we will compare Immediate Intervention participants relative

to Delayed Intervention participants in a random-effects regression using SAS PROC GLIMMIX The dependent variable will be the standardized Framingham risk score at 15-month follow-up Initially, covariates will be limited

to the baseline risk score and intervention status So we will model participant i (i = 1, 2, , njk) under the care of physician j within clinic k as:

(1) Risk 1ijk = b 0 + b 1 Risk 0ijk + b 2 Int ijk + αj +βk + e ijk

where Risk 1ijk is the standardized risk score for the i-th participant at 15 months (time 1) cared for by physician j

in clinic k, Risk 0ijk is the risk score at baseline (time 0),

Int-ijk is the intervention vs control status of the i-th

partici-pant in the same clinic and under the same physician, b 0

is a constant term, b 1 is the coefficient associated with

impact of baseline risk, and b 2 is the coefficient associated

with the impact of the intervention αj represents the

ran-dom effect caused by physician j and βk is the random

clinic effect The error term e ijk follows normal

distribu-tion, N(0, σ2) The analysis will be conducted on an

inten-tion-to-treat basis The risk scores of participants lost to

follow-up will be set to the baseline or interim values

Alternative methods for handling missing data, such as

multiple imputation, may be used if appropriate Our

pri-mary hypothesis will be confirmed if the coefficient

asso-ciated with the intervention (b 2) is significantly less than

0, implying that the intervention decreased CHD risk

scores independent of the baseline level

In addition, we will evaluate a number of secondary topics

including: a) baseline differences in CHD prevention

practices, b) moderators and mediators of the

interven-tion effect, c) durability of the interveninterven-tion effect, and d)

cost effectiveness of the intervention For example, some

of the secondary hypotheses we will be testing include a)

at baseline, CHD prevention practices within the SMMC

fell significantly short of attaining guideline-based goals

for a range of risk factors; b) at baseline, adherence to

pre-vention guidelines varied directly by SES with adherence

being least likely among participants of the lowest SES; c)

implementation of the intervention had a greater impact

on participants of lower SES thus resulting in a reduction

on the magnitude of socioeconomic disparities in CHD

prevention; d) changes in patient dietary and exercise

hab-its were the largest mediators of the impact of the

inter-vention; and e) the change in risk factors attributable to

intervention was sufficient to achieve reasonable

cost-effectiveness relative to other medical therapies

In the current manuscript, we presented comparisons of

baseline characteristics between the two study arms All

statistical analyses were performed in SAS for Windows

(SAS Institute, Cary, NC) Frequency distributions,

per-centages in each group of categorical variables, and means

and quartiles for continuous variables were generated for

both intervention groups Student's t tests were performed

on continuous variables and χ2 tests on categorical

varia-bles to assess comparability between the intervention

groups at baseline Statistical significance was set at p <

0.05 (two-tailed)

We will add appropriate covariates into equation (1) to

perform the testing of the secondary hypotheses related to

moderators and mediators of the intervention effect For

example, these covariates may include SES, change in

caloric intake, and change in physical activity The

cost-effectiveness analysis will include: measurement of costs,

measurement of changes in quality-adjusted life years

(QALYs), and calculation of a cost-effectiveness ratio with

an appropriate confidence region The cost of

implement-ing HTH will be estimated based on the cost of HTH staff time whereas the cost of implementing usual care will be derived from SMMC administrative records We will esti-mate a statistical model of QALY changes based on the change in risk of death and, among survivors, the reduc-tion in quality of life due to non-fatal events, which will

be approximated using the collected health care utiliza-tion data Using the cost and QALY figures we will esti-mate an incremental cost-effectiveness ratio, representing the cost per QALY due to the intervention, and a 95% con-fidence region surrounding the cost-effectiveness ratio using a bootstrapping method Sensitivity analyses will be performed by varying the underlying model assumptions

Results

We achieved equal distributions of the demographic, bio-physical and lifestyle characteristics between the two intervention groups Each of these categories is reviewed below, with an emphasis on the aggregate characteristic of the entire population

Demographic characteristics (Table 2)

The mean age of HTH participants at baseline was 56 years (range 31 to 85 years) One participant whose age was 31 years at enrollment was randomized because of an incor-rect date of birth, which was later incor-rectified We had expected to recruit an ethnically diverse population, including Latinos/Hispanics (55%) and other minorities (25%) The final sample consisted of 63% Latinos/His-panics, 12% Asians and Pacific islanders, and 10% African Americans In addition, 65% of the participants were female, 61% had less than a high school education, and 62% were not employed at the time due to unemploy-ment, disability or retirement This demographic profile differs from that of San Mateo County and of the U.S as being more ethnically diverse and socioeconomically dis-advantaged

We also examined the distribution of participants by gen-der and ethnicity (Latinos/Hispanics vs others) across the four study sites The distribution of gender was compara-ble among clinics with women accounting for 59% of the participants in the South San Francisco clinic (total n = 100), 62% in the Menlo Park clinic (109), and 70% in the Redwood City (127) and Daly City clinics (83) The distri-bution of ethnicity varied across clinics Eighty-seven per-cent of participants from the Redwood City clinic were Hispanic, accounting for 42% of all Hispanics in the entire sample In addition, 78% of all blacks in the sample were from the Menlo Park clinic

Biophysical and lifestyle factors (Figure 2 and Table 3)

Twenty percent of participants in both the Immediate Intervention and Delayed Intervention groups reported having a prior CVD event Sixty-three percent of

partici-pants had been diagnosed with diabetes, and an

addi-tional 22% had metabolic syndrome according to the

Adult Treatment Panel III definition[23] The average

10-year CHD risk was 15% (95% confidence interval [CI]:

13–16%) among HTH participants, with a median risk of

11% (interquartile range: 7–20%) Nearly 70% of

partici-pants in either group had a BMI > 30 kg/m2, with the

mean BMI of 34.5 kg/m2 LDL-C levels averaged 104 mg/

dL (95% CI: 100–108 mg/dL) with an interquartile range

of 81 to 122 mg/dL Depressed HDL-C, elevated TC:HDL

ratio, elevated TG, and elevated SBP were common among

participants In particular, three-quarters of the

partici-pants had TG levels over 130 mg/dL or a TG:HDL ratio

over 3.0, both suggesting insulin resistance [35] In

addi-tion, 16% of participants self-identified as current

smok-ers, and 45% had a family history of CHD or stroke On

average, HTH participants reportedly consumed 3.4

serv-ings of fruits and vegetables per day, whereas their daily

consumption of high-fat foods approached 4 servings

These participants also reported a daily average of 26

min-utes of moderate- or vigorous-intensity physical activity

We observed that several significant differences in

bio-physical and lifestyle factors by sex and ethnicity (Table

4) Women had lower 10-year risk for CHD than men

(13% vs 18%; p < 0.0001) When we removed the impact

of gender on risk by calculating 10-year CHD risk for

women using the male algorithm and vice versa, however,

we found comparable levels of risk factor burden between two genders Other gender differences included higher BMI and HDL-C levels, lower TC:HDL and TG:HDL ratios, and less physical activity in women compared with men Compared with non-Hispanics, Hispanics had higher val-ues of TC:HDL ratio, TG, and number of minutes of mod-erate- or vigorous-intensity physical activity

Baseline medical therapies (Figure 3)

Prior to randomization, a large proportion of participants were taking medications for specific medical conditions Eighty-nine percent of participants who had been diag-nosed with hypertension received prescriptions for anti-hypertensive medications, and 69% of those with hyperlipidemia were prescribed lipid-lowering medica-tions Insulin or oral hypoglycemic agents were prescribed among 88% of participants with diabetes mellitus Also, 64% of those with CVD or diabetes were taking aspirin The proportion being treated at baseline for the selected conditions did not differ by sex and ethnicity

Discussion

As expected, the randomization process in the HTH effec-tively achieved an essentially equal distribution of socio-demographic, clinic and lifestyle characteristics between the two intervention groups The lack of statistically and

Table 2: Demographic characteristics of HTH participants relative to San Mateo County and the U.S population 1

Married/Living with a

Partner

Disabled or Otherwise Not in Labor Force

and 85.

clinically significant differences on major potential

con-founders provides strong assurance for the internal

valid-ity of the clinical trial The HTH sample is unique in its

high composition of Latinos/Hispanics (62%) and other

ethnic minorities (22%), persons with low educational

attainment (61%), and persons without employment

(62%) These population groups are clearly labeled in the

literature as priority populations disproportionately

affected by CVD and who are more likely to receive

infe-rior CVD care [1,4,5] The HTH sample exceeded our pro-posed target of enrollment for women (50%) and Latinos/Hispanics (55%) In addition, our sample con-sisted of 12% Asians and Pacific Islanders (target: 16%) and 10% African Americans (target: 10%)

By design, major cardiovascular risk factors are highly prevalent among HTH participants 10-year CHD risk averaged 18% in men and 13% in women despite a mod-est LDL-C level and a high on-treatment percentage at baseline This should not be surprising given that 63% of participants were diagnosed with diabetes, and an addi-tional 22% with metabolic syndrome In addition, many participants had depressed HDL-C levels and elevated val-ues of TC:HDL ratio, TG, TG:HDL ratio, and blood pres-sure Furthermore, nearly 70% of participants were obese, 45% had a family history of CHD or stroke, and 16% were current smokers

A high proportion of the participants in our study were female (65%) although males are likely to be at higher risk for CAD This reflects the overall higher usage of out-patient health care by women compared to men, as well

as the greater availability of women for appointments dur-ing daytime workdur-ing hours To increase participation of men in future trials, setting aside evening clinic hours would enable men to come to appointments after their workday In addition, case finding through women may lead to participation of their husbands although this would impose a more complex analytic design to account for the involvement of multiple household members in the same study

Proportion of randomized participants with CVD and CVD

risk factors

Figure 2

Proportion of randomized participants with CVD and CVD

risk factors *In the absence of diabetes **FH: family history

of cardiovascular disease

0%

20%

40%

60%

80%

100%

CVD

Diab

etes

M

abo

lic

yndr

om e*

B

>140/

90 LD 130

TG>14 0 HD L<5 0 BM I>30 Sm ng FH

CV

Immediate Intervention (N=212) Delayed Intervention (N=207)

Table 3: Descriptive statistics for biophysical and lifestyle factors by study group 1

Fruits and Vegetables (#/

day)

Moderate and Vigorous

Physical Activity (minutes/

body mass index; LDL-C low density lipoprotein cholesterol; HDL-C high density lipoprotein cholesterol; TC total cholesterol; TG triglyceride; HbA1c hemoglobin A1c; SBP systolic blood pressure; DBP diastolic blood pressure.

The cardiovascular health profile of the HTH cohort

strongly suggests a need for intensive cardiovascular risk

reduction interventions, particularly lifestyle risk factor

interventions The interrelatedness of cardiovascular risk

factors demands an integrated approach to management

However, the current US health care system lacks the

capa-bility of providing effective and cost-conscious CVD risk

reduction interventions, particularly for ethnic minorities

and low-SES populations [4-6] Chronic disease

manage-ment exerts tremendous time demands on PCPs [3,36]

such that achieving guideline-accordant practice is

unlikely unless physicians work as part of a health care

team in which there is efficient division of labor Case

management provides an excellent team-approach model

for integrating multiple risk reduction into practice that strives to meet nationally established goals for CVD risk reduction Compared to usual care, case management has been shown to improve the delivery of care as well as resulting cardiovascular outcomes among predominantly white, high-risk patients [7-10] Data are only beginning

to accumulate with regard to the effectiveness of case management among ethnic minorities [11]

The HTH case management program is based on a model that has evolved through several previous clinical trials [7,8] The model provides a systematic approach to the comprehensive, individualized and intensive manage-ment of cardiovascular risk in at-risk patients It is based

on the premise that cardiovascular risk reduction is syner-gistic and that CVD prevention and management is most successful when lifestyle interventions are integrated with appropriate medical therapies At the core of the model is

a team of nurses and dietitians (case managers) capable of treating hypertension, dyslipidemia, diabetes, obesity, physical inactivity, and smoking cessation Case managers provide long-term counseling based on clinical status, risk level, interest in and readiness for change, and personal resources Case managers' activities are integrated with the activities of the patient's PCP Case management goals are modeled on latest practice guidelines

To conclude, baseline characteristics of HTH participants suggest that we have recruited an appropriate cohort in which to implement a case management approach and test its efficacy and cost-effectiveness Due to its unique composition of ethnic minorities and persons of low-SES, the HTH will enrich the U.S literature regarding better strategies for CVD prevention among these priority

popu-Table 4: Differences in biophysical and lifestyle factors by gender and ethnicity 1

N = 263

Non-Latino/Hispanic

N = 156

Proportion of randomized participants with specific

diag-noses who were prescribed appropriate medication at

base-line

Figure 3

Proportion of randomized participants with specific

diag-noses who were prescribed appropriate medication at

base-line

0%

20%

40%

60%

80%

100%

Antihypertensives for

HTN

Lipid-lowering Drugs for Hyperlipidemia

Insulin/Oral Agents for DM

Aspirin for CVD/DM

Immediate Intervention Delayed Intervention